Jarrod Luze Black Hills Power Rapid City, South Dakota Distribution Transformer Size Optimization by Forecasting Customer Electricity Load Jarrod Luze Black Hills Power Rapid City, South Dakota Good Morning. I’m Jarrod Luze, and I am presenting on the technical paper “Distribution Transformer Size Optimization by Forecasting Customer Electricity Load” - This is a project that I worked on as an engineering intern at Black Hills Power – an electric utility based in Rapid City, South Dakota. - I will continue to work for Black Hills Power until May; At that time I will start my full-time career as a Graduate Engineer for Ulteig Engineers in Sioux Falls, SD. - I’ve attended the South Dakota School of Mines and Technology and will be graduating May 9th with a Bachelor’s degree in Electrical Engineering.

Introduction Electric utilities face common challenges determining transformer sizes. Study consists of 960 three phase pad-mounted transformers. Research and categorization of existing transformers Ideal vs. actual benefit/cost analysis Forecasting future customer power demand As you all know, electric utilities face many challenges when selecting an appropriate size transformer for a given contractor and client. This report takes a look at the excess costs associated with inaccurate transformer sizing by Analyzing 960 three-phase padmount transformers - The Black Hills power transformers were categorized based on their customer load and name-plate ratings - A benefit/cost analysis was conducted based on the ideal and actual size of the transformers in use - A study based on actual customers in Rapid City is provided to aid the ability to forecast customer power use.

Study of Existing Transformers in Service Compared kVA name-plate rating to peak demand of customer ‘R+_’ signifies that a transformer is undersized and would ideally require a larger transformer for the load. ‘R-_’ signifies the transformer is under-loaded, and a smaller transformer would suffice. Initially, we studied the existing transformers and created a size index. The kVA name-plate rating was compared to the actual peak demand of the customer being supplied. The categories are based on an ‘R+ and ‘R-’ rating scale. R+ signifies that a transformer is connected to a load greater than the rating of the transformer, while an ‘R-’ rating signifies that a transformer is too big. For example: If a transformer supplying a customer was rated at 500 kVA, and the customer was drawing between 501 and 750 kVA, an R+1 category would be assigned to that transformer.

Study of Existing Transformers in Service Out of 960, 605 were oversized-63% Over 10% at least 3 sizes too big 150 kVA, 300 kVA and 500 kVA are the least accurately sized Very few transformers over-loaded Overall results of study show an overly conservative sizing method After compiling all of the categorized data, the results of the study show that out of the 960 three-phase padmount transformers studied, 63% were oversized and 10 % of the transformers were 3 categories larger than necessary. *Analysis showed that the 150 kVA, 300 kVA, 500 kVA and 750 kVA transformers were the least accurately sized groups. *Very few transformers were considered over-loaded, showing that the methods of sizing were overly conservative.

Existing Transformers in Service This chart is a visual representation of the resulting categorized transformers. The green stands for the ideally sized transformers, while the shades of blue and black show the varying levels of sizing inaccuracy.

Study of Existing Transformers in Service This table shows the exact number of transformers and corresponding categories. Out of the 300 kVA transformer group, 258 out of 287 transformers are oversized, that’s 89%. Out of 116 - 500 kVA transformers, 86 are considered oversized – 74%

Financial Analysis Capital expense of the equipment Operating cost = No-load power loss Wholesale electricity rate of $0.04/kWH was used After analyzing the data gathered from the 960- 3-phase padmounts, a benefit/cost comparison was made between the actual expenses of the transformers at there current loads and the ideal situation of perfectly sized transformers. This study considers the Capital expense of the equipment and the operation and maintenance costs, based on the wholesale electricity rate of 4 cents per kilowatt hour.

Financial Analysis – Capital Estimated by using the price of the most recently purchased transformer of that size Sums entire purchase price* of the 960 transformers (total capital expense) *Purchase price includes installation costs Theoretical estimated purchase cost vs. actual estimated purchase cost The Capital expense analysis was conducted by using the price of the most recently purchased transformer of each size. The total purchase cost refers to the sum of the 960 transformer’s initial price – the value also includes installation costs. Theoretical purchased cost and actual purchase cost estimates were compared to illustrate the capital advantages of ‘right’ sizing transformers. At Black Hills Power, if the 960 3-phase, padmount transformers were sized ideally, over an estimated $967,000 would have been spared in initial purchase cost.

Financial Analysis The total estimated actual purchase cost of the transformers studied adds up to $5.6 million, while the theoretical purchase cost under ideal conditions, totals about 1 million dollars less at 4.6 million - Savings of 17%

Financial Analysis – Operating No-load power loss (Watts) Not considered: Full-load loss, repairs and maintenance Conservative estimate PF of 0.95 used, if unable to gather from database When looking at the operating expense benefits of accurate transformer sizing, the No-load-power loss was considered. This study did not consider Full-load loss, and repairs or maintenance costs – therefore delivering a conservative estimate

Financial Analysis No-Load Power Loss (O&M) Looking at the No-load power loss, the annual actual total cost is about $165,000. If ideally sized, the transformers would total a no-load loss annual expense of $113,000 Resulting in a benefit of $52,000 annually – over 30% of actual N0-Load Loss expense.

Financial Analysis - Overall Assuming sizing methods and results are consistent for all BHP transformers Three-phase, pad-mount share of the transformer purchase cost is roughly 26% of the $2.5 million annual transformer purchase cost budget At 17%, $425,000 annual benefit Black Hills Power utility has an 2.5 million dollar transformer purchase cost budget covering all single-phase, three-phase, pole-mount and pad-mount transformers. The three-phase padmount makes up roughly 26% of that annual budget. When assuming the sizing methods and results are fairly consistent for all Black Hills Power transformers, the 17% benefit results in an estimated $425,000 in annual savings in the transformer purchasing budget.

Research Application Increase efficiency from the sizing statistics Possibilities Review current transformer placement, and change-out existing units based on economic feasibility. Develop more accurate transformer sizing method After analyzing the sizing data and cost analysis, there are some options when deciding what type of actions will increase efficiency regarding transformer expenses. One option would be to review the current transformer placements and to change-out existing units on a case-by-case basis. However, the feasibility of this action requires deeper research and depends on individual transformer situations and environments. This study focuses on the more obvious solution of developing more accurate transformer sizing methods going forward.

Forecasting Customer Electricity Loads Many factors Size of structure to be powered General purpose of structure Structural components Machines and Appliances to be installed Location Personnel capacity of building or structure Obviously there are many factors that determine what a customer’s power use is going to be. This study generalizes these characteristics into categories.

Customer Categories This study includes Retail Stores Business offices Apartments (gas heated, electric heat) Many others to be considered, time-constraints limit this study This study takes a look at the power demand characteristics of 3 categories: Retail stores, Business offices and apartment complexes. Many other categories of customers exist but due to time constraints were unable to be researched.

Data Collection and Calculation Cooperation of Customers Tax Equalization office supplied square footage information Averages based on Peak kVA demands Power factor assumed 0.95 if Unavailable in database Calculations of W/sf, mA/sf Consistent values, low standard of deviation in data Data was collected on square feet measurements of buildings and Main service panel amperages of several establishments supplied by Black Hills Power in Rapid City, SD. Area measurements of the customer buildings were supplied by the Tax Equalization Office at the courthouse. The peak power demands of customers were used and calculations of Watts per square foot and milliamps per square foot were developed. Data was gathered on all customers where sufficient information was available and clear.

Results – Business Offices Averaged 5.76 watts per square foot Highest: 7.09 Lowest: 4.52 W/sqft Averaged 34% of Main Switch Ampacity Mainly fluorescent lighting Gas heated The results of the Business Office calculations and estimates showed: -An average of 5.76 watts per square foot power demand while the highest and lowest average was 7 and 4.52 respectively. - the average amperage was 34% of the Main service panel’s Ampacity.

Business Offices These are the data results in table form for the Business Office category. Business office category was largely comprised of Law offices, realtor offices, medical offices, and government office facilities.

Results - Retail Stores Averaged 4.98 W/sqft High: 8.13 / Low: 2.86 Averaged 46% of Main Switch Ampacity Mostly Fluorescent Lighting, some spot lighting Results of the Retail store category showed an average of 4.98 watts per square foot demand factor, while the outliers were 8 and 2.86 watts per square ft.

Retail Stores The retail store category had many data points to analyze from. The stores that make up this category were largely Bookstores, department stores, and arts and crafts stores.

Results - Apartments Gas Heated, summer peaking, 94.7% occ. Averaged 1.42 W/sqft, 1.5 W/sqft @ 100% High: 2.09 / Low: 0.82 Electric Heat, winter peaking, 81.5% occ. Averaged 3.53 W/sqft, 4.3 W/sqft @ 100% High: 4.14 / Low: 2.71 The Apartment complex results showed key discrepancies between Gas Heated apartments that had summer peaking loads and Electrically heated apartments with winter peaking loads. The Gas Heated apartments averaged 1.42 watts per square feet while the electric heated apartments averaged 3.53 watts per square feet.

Apartment Buildings This table shows the results of the Apartment building data. The Orange highlighted area at the top are the electric heated buildings while the gas heated are in plain color.

Applications Gives utility representatives statistics when discussing options with customers & contractors. Presents evidence & factual history to help decide on transformer size. Provides foundation and structure for further research of future demand and transformer sizing. The categorized watts per square foot values and other customer load data and can be applied to a utilities operations by: Supplying utility representatives with statistics and research for discussion and decision making purposes when discussing construction options. It presents evidence and factual history to help decide on transformer size, while also providing a foundation for further research of future demand and transformer sizing.

Summary Sizing analysis shows significant cost avoidance capabilities: 17% $425,000 O&M savings (NLL only) of 31% Customer demand indicators may help utility reps with transformer sizing, and provide a basis to advance research After analyzing presented research based on the 960 three-phase pad-mount transformers owned and operated by Black Hills Power, the following assessments can be made. -From the sizing analysis results in the transformer loading study, there is the capability of significant cost avoidance -17% savings, or, a total of $425,000 in annual transformer purchase expenses -No-load-loss savings of 31% yearly -From researching the various customer categories, peak demand indicators may help utility reps with transformer sizing and provide a basis from which to extend further research opportunities.

Questions?